The Relationship between Optimism and Mindfulness with Cognitive Performance in Older Adults by Sanaz Ghannadi, Morteza Tarkhan

“…Furthermore, 34% of the variance in cognitive function was explained by optimism and mindfulness.Conclusion: Therefore, based on the findings of the present study, it can be concluded that optimism and mindfulness are important variables in predicting cognitive function (p < 0.05).…”
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Elevator Control Simulation Using Fuzzy Logic Management by Mehr Ali Qasimi, Asmatullah Nashir

“…Within a set of fuzzy rules, three important linguistic variables are added to improve the performance of the elevator group. …”
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Can digital transformation improve the transparency and accountability of Indonesian public governance? by M. Irwan Tahir, Ani Martini, Anak Agung Ngurah Gunawan, Yogi Makbul, Nirma Yossa, Wisber Wiryanto, Moch Fahrudin, Rahmat Ilya

“…Public administration can increase transparency, efficiency, public participation and data-based decision-making. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…This study investigates an advanced diagnostic strategy to assess particulate filter health based on resistive soot sensors and available engine variables. The sensor data are projected to generate a 2D signature that reflects the changes in filtration efficiency. …”
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Gut health modulation through phytogenics in poultry: mechanisms, benefits, and applications by Aderanti Ifeoluwa Oni, Oyegunle Emmanuel Oke

“…These plant-derived compounds, such as polyphenols, alkaloids, flavonoids, and essential oils exhibit various bioactive properties that improve gut microbiota composition, support immune function, and improve nutrient absorption by influencing gut morphology and digestive enzyme activity. …”
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Compilation of the Accelerated Test Spectrum of Transmission based on Low Loading Strengthening Effect by Zou Xihong, Yang Zhenliang, Yuan Dongmei, Peng Jigang, Zhou Yujun

“…The indoor simulation bench test of transmission is an important method of assessment,evaluation and promotion of its performance.Taking transmission as an example,a program load spectrum compiling method for transmission accelerated fatigue test is presented.The actual road load spectrum of automobile transmission is collected on Automobile Proving Ground in Dianjiang used wireless telemetry technology.The actual load spectrum is pretreated divided gear position,the second gear load spectrum is selected as an example.The frequency distribution matrix of load is obtained based on rainflow counting method,the distributions of mean and range are found to confirm with normal distribution and two- parameter Weibull distribution respectively.The mean of the normal distribution is 91.77 N·m,and the standard deviation is 163.27 N·m,the shape parameter of Weibull distribution is 1.346,and the scale parameter is 305.489,the distributions of load range and mean is independent.The two- dimensional load spectrum with 8×8 levels is established with joint probability distribution function.After two- dimensional load spectra is transformed into one- dimensional 8-level load spectra with variable mean method.Based on damage and low loading strengthening property of half shaft,the equivalent strengthening rule between strengthening loads is explored.By transferring the strengthening loads to the most effective level,the load loading frequency reduced,test efficiency is improved.…”
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Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications by Aditya Venkatraman, Mark A. Wilson, David Montes de Oca Zapiain

“…This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.…”
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Dynamic Gesture Recognition Algorithm Combining Global Gesture Motion and Local Finger Motion for Interactive Teaching by Li Jiashan, Li Zhonghua

“…Aiming at the problems of complex time sequence and spatial variability of dynamic gestures, this paper proposes a gesture recognition method combining global motion and local motion of fingers. …”
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Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor by Santiago Rómoli, Mario Serrano, Francisco Rossomando, Jorge Vega, Oscar Ortiz, Gustavo Scaglia

“…The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies. …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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Parametric Survival Models of Hemodialysis Patients in Relation with Patient-Related Factors by Reem Yousif MEKKI, Mohamed Hassan MUDAWI, Manahil Saidahmed MUSTAFA, Altaiyb Omer Ahmed MOHMMED, Ahmed Bakheet Abd ALLA, Abdel Rahman AHMED

“…Based on the Cox-Snell Residuals and AIC, BIC, and Gompertz (PH) model is an efficient model than other when the values of (AIC=662.21), (BIC=703.83) and (R2=0.211) where maintained Study assessed that the variables dealing with univariate models were signifi cant but had a signifi cant effect on hemodialysis survival. …”
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Multi-Scale Multi-Domain Hybrid Finite Element Modeling of Light Propagation by Jingwei Wang, Zhanwen Wang, Lida Liu, Yuntian Chen

“…We revisit finite element method of modeling multi-scale photonic/electromagnetic devices via the proposed beam basis function, in combination with domain decompositions. …”
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Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. These features are combined through a fusion layer, and a customized loss function is employed to accurately predict fitness scores.ResultsExtensive experimental evaluation demonstrates that the proposed model consistently outperforms competitive baseline models. …”
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Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases by Adel M. Hemeida, Mohammed S. Al-Blehed, Saad El-Din Desouky

“…The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. A great deal of the unlimited what if questions can be answered using this model. …”
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Flow-based cytometric analysis of cell cycle via simulated cell populations. by M Rowan Brown, Huw D Summers, Paul Rees, Paul J Smith, Sally C Chappell, Rachel J Errington

“…We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. …”
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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. …”
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A LINEAR SIMULATION MODEL FOR OPTIMIZING CROP STRUCTURE IN ORDER TO MAXIMIZE INCOME IN A VEGETAL AGRICULTURAL FARM by Sorin IONITESCU

“…The model included: the 8 unknown variables for the cultivated area with 8 crops: wheat, rye, barley, peas, rape, soybean, maize and sunflower, 14 restrictions regarding Diesel fuel, fertilizers, herbicides, total surface, expenditures, income, and area per each crop, and objective - function f(Max) Income. …”
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Mechanical Properties and Statistical Damage Constitutive Model of Rock under a Coupled Chemical-Mechanical Condition by Yun Lin, Feng Gao, Keping Zhou, Rugao Gao, Hongquan Guo

“…To investigate the mechanical damage evolution process of rock under a coupled chemical-mechanical (CM) condition, an improved statistical damage constitutive model was established using the Drucker-Prager (D-P) strength criterion and two-parameter Weibull distribution. The damage variable correction coefficient and chemical damage variable which was determined by porosity were also considered in the model. …”
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Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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Developing data driven framework to model earthquake induced liquefaction potential of granular terrain by machine learning classification models by Kennedy C. Onyelowe, Viroon Kamchoom, Tammineni Gnananandarao, Krishna P. Arunachalam

“…The high precision and Phi Correlation Coefficient further affirm the reliability and accuracy of the model’s predictions. …”
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